(Anglais) In this paper, a multiobjective decision-making process is modeled by a multiobjective fuzzy linear programming problem with fuzzy coefficients for the objectives and the constraints. Moreover, the decision variables are linked together because they have to sum up to a constant. Most of the time, the solutions of a multiobjective fuzzy linear programming problem are compelled to be crisp values. Thus the fuzzy aspect of the decision is partly lost and the decision-making process is constrained to crisp decisions. We propose a method that uses fuzzy decision variables with a joint membership function instead of crisp decision variables. First, we consider lower-bounded fuzzy decision variables that set up the lower bounds of the decision variables. Then, the method is generalized to lower–upper-bounded fuzzy decision variables that set up also the upper bounds of the decision variables. The results are closely related to the special type of problem we are coping with, since we embed a sum constraint in the joint membership function of the fuzzy decision variables. Numerical examples are presented in order to illustrate our method.